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‘DeHate: A Stable Diffusion-based Multimodal Approach to Mitigate Hate Speech in Images’ (arXiv) introduces a new multimodal dataset and a framework called DeHate to combat hate speech embedded in images. The method uses stable diffusion and a Digital Attention Analysis Module (DAAM) to identify and then blur the offensive parts of a picture.

Next, ‘Escalation of Hate Speech in the Media Due to Political Crisis’ (ANEM) is a study in Serbia that found a sharp increase in hate speech in the media following a political crisis, with public authorities and media outlets being the main purveyors of these narratives. The most common targets were women and political opponents, with the rhetoric becoming more complex and blending political, racial, and gender prejudice.

‘Beyond Hate Speech: Online Rumors and Out-Group Resentment in Divided Societies’ (Comparative Political Studies) then demonstrates that even minor, non-hateful online rumors can significantly worsen intergroup tensions in divided societies. Specifically, rumors framed around perceived injustice have the power to dramatically change group sentiments and amplify conflict-related emotions.

On the other hand, ‘When words become weapons: How hate speech threatens democracy’ (International Idea) examines how hate speech endangers democratic institutions by weakening social cohesion, inciting violence, and silencing dissenting voices. It argues for a multifaceted approach—including legal, educational, and civic measures—to combat online hate while upholding the distinction between protected free expression and unlawful incitement.

Finally, ‘Examining the Effects of Language Misuse and Hate Speech on Individuals and Corporate Organisations’ (AJHCER) confirmed that hate speech and language abuse are highly correlated and have measurable negative social, psychological, and corporate impacts. It concludes that hate speech is a form of improper language use and advocates for severe, strategic, and technology-driven countermeasures.

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